Secondary Data Analyses for Substance Abuse Research

描述（由申请人提供）：重复暴露于滥用药物会导致大脑奖励回路的稳定变化，这将进一步导致行为异常，如依赖、敏感和渴望。了解药物成瘾的分子生物学将为治疗药物成瘾和预防新成瘾者的流行提供改进的疗法。研究表明，大脑中基因表达的变化有助于稳定调节与药物成瘾有关的大脑奖赏回路。然而，这种调控的具体基因和转录机制仍然知之甚少。该应用程序的总体目标是通过综合分析与药物成瘾相关的丰富生物数据集，深入了解药物成瘾的分子机制。大量的全基因组分子谱数据集已经积累到研究药物成瘾。这些大规模的数据为产生重要的科学发现提供了巨大的机会，但也为数据分析带来了巨大的挑战。来自其他研究领域的研究，特别是癌症研究，已经表明，有效地整合各种分子谱数据集不仅可以增加数据分析的能力，还可以提供更全面的生物学过程知识。本研究的中心假设是，药物成瘾相关的分子谱数据集的综合分析将导致对药物成瘾的分子机制和重要基因和途径的新发现的系统理解。这项研究将集中在可卡因成瘾，因为可卡因是最突出的非法药物滥用，并在可卡因成瘾积累了大量的分子谱数据。然而，所提出的方法将是通用的，并适用于研究其他药物成瘾。总之，该项目将提供：（1）更好地从机理上了解可卡因成瘾;（2）用于综合分析吸毒成瘾数据的强大统计/计算工具;（3）用于加强吸毒成瘾研究的更广泛知识基础设施的综合数据库。 公共卫生相关性：了解药物成瘾的分子生物学将为治疗药物成瘾和预防新成瘾者的流行提供改进的疗法。该项目将提供对可卡因成瘾的更好的机械理解，并提供一个全面的数据库，以加强药物成瘾研究的更广泛的知识基础设施。

DESCRIPTION (provided by applicant): Repeated exposure to a drug of abuse causes stable changes in the reward circuitry of the brain, which will further lead to behavioral abnormalities such as dependence, sensitization and craving. Understanding the molecular biology of drug addiction will provide improved therapies to treat drug addiction and prevent the epidemic of new addicts. It has been shown that gene expression changes in brain contribute to the stable regulation of the brain's reward circuitry involved in drug addiction. However, the specific genes and the transcriptional mechanisms underlying such regulation remain poorly understood. The overall goal of this application is to provide deeper insights into the molecular mechanisms of drug addiction by integrated analysis of rich biological data sets related to drug addiction. A large amount of genome-wide molecular profiling datasets have been accumulated to study drug addiction. These large scale data provide great opportunities to generate significant scientific findings, but also great challenges for data analysis. Studies from other research areas, especially cancer research, have shown that integrating the various molecular profiling datasets effectively can not only increase the power of data analysis, but also give more comprehensive knowledge of the biological process. The central hypothesis of this study is that integrated analysis of drug addiction related molecular profiling datasets will lead to a systematic understanding of the molecular mechanisms and novel findings of important genes and pathways involved in drug addiction. This study will focus on cocaine addiction because cocaine is among the most prominent illicit drugs of abuse, and considerable molecular profiling data have been accumulated in cocaine addiction. The proposed methods, however, will be general and applicable to study other drugs of addiction. In summary, this project will provide: (1) better mechanistic understanding of cocaine addiction; (2) powerful statistical/computational tools for the integrated analysis of drug addiction data; and (3) a comprehensive database for strengthening the broader knowledge infrastructure for drug addiction research. PUBLIC HEALTH RELEVANCE: Understanding the molecular biology of drug addiction will provide improved therapies to treat drug addiction and prevent the epidemic of new addicts. This project will provide better mechanistic understanding of cocaine addiction, and a comprehensive database for strengthening the broader knowledge infrastructure for drug addiction research.